OpenSearch Query Profiler

A Streamlit web application for analyzing OpenSearch query performance with interactive visualizations.

Features

• Live Query Execution: Connect to OpenSearch clusters and execute queries with profiling
• Profile Analysis: Analyze existing profile responses from queries run elsewhere
• Phase Timing: View query & fetch phase breakdowns with phase_took metrics
• Shard Performance: Identify slowest performing shards
• Component Analysis: Drill down into queries, collectors, and aggregations
• Interactive Charts: Copyable labels and detailed breakdowns

Interface

The app provides comprehensive query performance analysis with:

• Query & Fetch phase timing metrics
• Shard performance overview (top 10 slowest)
• Component-level analysis with interactive charts
• Detailed shard breakdowns with operation timings

Installation

pip install streamlit requests plotly
streamlit run app.py

Access at http://localhost:8501

Usage

Live Profiling

1. Enter OpenSearch endpoint and index
2. Modify the query JSON as needed
3. Click "Execute" to run and analyze

Analyze Existing Profile

1. Paste OpenSearch profile response JSON
2. Click "Analyze Profile"
3. View comprehensive performance breakdown

Requirements

• Python 3.7+
• streamlit
• requests
• plotly

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.